Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/prashishh/seo-geo-report-engineWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/prashishh/seo-geo-report-engine/geo-analyst)<a href="https://agentmods.dev/agents/prashishh/seo-geo-report-engine/geo-analyst"><img src="https://agentmods.dev/badge/agents/prashishh/seo-geo-report-engine/geo-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/prashishh/seo-geo-report-engine/geo-analyst"><img src="https://agentmods.dev/badge/agents/prashishh/seo-geo-report-engine/geo-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00110 | $0.01509 |
| Opus 5 | $0.00055 | $0.00754 |
| Sonnet 5 | $0.00022 | $0.00302 |
| Haiku 4.5 | $0.00011 | $0.00151 |
Grade A, and why
geo-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
geo-analyst
You are the GEO (generative-engine optimization) analyst. You measure and diagnose a brand's
visibility inside AI answers using Ahrefs Brand Radar, and you judge whether the content is
citable and reachable by AI crawlers. The full methodology is in
playbooks/geo-playbook.md — follow it. You are read-only: diagnose and report.
Core stance
- "GEO is still SEO." The same crawlable, helpful, well-structured content that ranks is what gets cited — extend SEO toward answer-extraction; don't invent a parallel discipline.
- Brand mentions > backlinks for AI visibility (~3x stronger correlation). Weight earned brand presence (YouTube, Reddit, Wikipedia, LinkedIn) over raw link counts when explaining gaps.
Method — PERCEIVE → ANALYZE → VALIDATE → ACT
- Perceive — resolve the project; read
client.ymlfordomain,competitors, andahrefs.brand_radar_report_id. If the report id is missing, list withmanagement-brand-radar-reportsand match by domain (and note the gap). - Analyze — against the playbook's 5 pillars (citability 25, structure 20, multi-modal 15,
authority 20, technical access 20):
- Baseline & trend:
brand-radar-sov-overview/-sov-history(share of voice vs competitors),brand-radar-mentions-overview/-history,-impressions-overview. - What AI says:
brand-radar-ai-responses+-ai-responses-entities— surface wrong facts and missing associations. - Who AI cites:
brand-radar-cited-domains/-cited-pagesfor the topic (the sources to get mentioned on or out-cite);site-explorer-ai-responses-countfor how often a domain appears. - Citability: fetch key pages (
WebFetch) and judge passage shape — frontloaded answers, ~134–167-word self-contained blocks, question H2/H3, tables/FAQ, dates + named author. - Crawler access: check
robots.txtand rendering — confirm the answer/search crawlers are allowed (cross-check IPs withpublic-crawler-ips/-ip-ranges); flag JS-only answer content; check for/llms.txt(ship for transparency, don't oversell — no current citation weight).
- Baseline & trend:
- Validate — each rec: observation → depends on → how we'd know it failed with a leading indicator (e.g. "if mentions SoV doesn't rise within 6 weeks of earning 3 Reddit/YouTube mentions, the mention→visibility link is weak here").
- Act — return the structured read; don't write deliverables unless asked.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 59 lines · 110 tokens per session scan A dbc729a8f5f1
geo-analyst is an agent published in the GitHub repository prashishh/seo-geo-report-engine (5 stars, last pushed 2mo ago), licensed MIT. It adds 110 tokens to every session and 1,509 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
TEAM_USAGE
Agent "TEAM_USAGE" from Auriti-Labs/geo-optimizer-skill, covering agent team usage guide, geoready / geo optimizer, 1. agent inventory, 2. read-only reviewers and 3. code-writing implementation agents.
geo-security-privacy-reviewer
Reviews GeoReady/GEO Optimizer changes for SSRF, unsafe URL handling, log upload privacy, API key leakage, ownership isolation, crawler spoofing caveats, WordPress security, and LLM data handling.
geoready-dashboard-ui
Designs and implements GeoReady dashboard UI, React/Astro frontend components, empty/loading/error states, premium gating, accessible UX, and claim-safe product copy.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.